More recent, Maxmin DQN [1]} addresses the overestimation bias using order statistics, using the ensemble size \(N\)  as a hyperparameter to tune between underestimating and overestimating bias. The target value for Maxmin DQN is calculated using
\(Q_M\left(\cdot ,\cdot \right) &= \min _{i= 1, \ldots , N} Q_i\left(\cdot , \cdot \right)\nonumber \\Y_t^M &= R_t + \max \limits _{a^{\prime }\in \mathcal {A}} Q_{M}\left(s_{t+1}, a^{\prime }\right)\) 
